Various X-ray baggage scanning systems are known for detecting the presence of explosives and other prohibited items in baggage, or luggage, prior to loading the baggage onto a commercial aircraft. A common technique of measuring a material's density is to expose the material to X-rays and to measure the amount of radiation absorbed by the material, the absorption being indicative of the density. Since many explosive materials may be characterized by a range of densities differentiable from that of other items typically found in baggage, explosives are generally amenable to detection by X-ray equipment.
Most X-ray baggage scanning systems in use today are of the “line scanner” type and include a stationary X-ray source, a stationary linear detector array, and a conveyor belt for transporting baggage between the source and detector array as the baggage passes through the scanner. The X-ray source generates an X-ray beam that passes through and is partially attenuated by the baggage and is then received by the detector array. During each measuring interval the detector array generates data representative of the integral of density of the planar segment of the baggage through which the X-ray beam passes, and this data is used to form one or more raster lines of a two-dimensional image. As the conveyor belt transports the baggage past the stationary source and detector array, the scanner generates a two-dimensional image representative of the density of the baggage, as viewed by the stationary detector array. The density image is typically displayed for analysis by a human operator.
Most explosives capable of significantly damaging an aircraft are sufficiently large in length, width, and height so as to be readily detectable by an X-ray scanner system regardless of the explosive's orientation within the baggage. Plastic explosives, however, present a particular challenge to baggage scanning systems. Due to their moldable nature, plastic explosives may be formed into geometric shapes that are difficult to detect. A plastic explosive powerful enough to damage an aircraft may be formed into a relatively thin sheet that is extremely small in one dimension and is relatively large in the other two dimensions. The detection of plastic explosives may be difficult because it may be difficult to see the explosive material in the image, particularly when the material is disposed so that the thin sheet is parallel to the direction of the X-ray beam as the sheet passes through the system.
Accordingly, a great deal of effort has been made to design a better baggage scanner. Such designs, for example, have been described in U.S. Pat. Nos. 4,759,047 (Donges et al.); 4,884,289 (Glockmann et al.); 5,132,988 (Tsutsui et al.); 5,182,764 (Peschmann et al.); 5,247,561 (Kotowski); 5,319,547 (Krug et al.); 5,367,552 (Peschmann et al.); 5,490,218 (Krug et al.) and German Offenlegungsschrift DE 31 503 06 A1 (Heimann GmbH).
At least one of these designs, described in U.S. Pat. Nos. 5,182,764 (Peschmann et al.) and 5,367,552 (Peschmann et al.) (hereinafter the '764 and '552 patents), has been commercially developed and is referred to hereinafter as the “Invision Machine.” The Invision Machine includes a CT scanner of the third generation type, which typically includes an X-ray source and an X-ray detector system secured respectively to diametrically opposite sides of an annular-shaped platform or disk. The disk is rotatably mounted within a gantry support so that in operation the disk continuously rotates about a rotation axis while X-rays pass from the source through an object positioned within the opening of the disk to the detector system.
The detector system can include a linear array of detectors disposed as a single row in the shape of a circular arc having a center of curvature at the focal spot of the X-ray source, i.e., the point within the X-ray source from which the X-rays emanate. The X-ray source generates a fan shaped beam, or fan beam, of X-rays that emanates from the focal spot, passes through a planar imaging field, and is received by the detectors. The CT scanner includes a coordinate system defined by X-, Y- and Z-axes, wherein the axes intersect and are all normal to one another at the center of rotation of the disk as the disk rotates about the rotation axis. This center of rotation is commonly referred to as the “isocenter.” The Z-axis is defined by the rotation axis and the X- and Y-axes are defined by and lie within the planar imaging field. The fan beam is thus defined as the volume of space defined between a point source, i.e., the focal spot, and the receiving surfaces of the detectors of the detector array exposed to the X-ray beam. Because the dimension of the receiving surfaces of the linear array of detectors is relatively small in the Z-axis direction the fan beam is designed to be relatively thin in the Z-axis direction. Each detector generates an output signal representative of the intensity of the X-rays incident on that detector. Since the X-rays are partially attenuated by all the mass in their path, the output signal generated by each detector is representative of the density of all the mass disposed in the imaging field between the X-ray source and that detector.
As the disk rotates, the detector array is periodically sampled, and for each measuring interval each of the detectors in the detector array generates an output signal representative of the density of a portion of the object being scanned during that interval. The collection of all of the output signals generated by all the detectors in a single row of the detector array for any measuring interval is referred to as a “projection,” or equivalently as a “view,” and the angular orientation of the disk (and the corresponding angular orientations of the X-ray source and the detector array) during generation of a projection is referred to as the “projection angle.” At each projection angle, the path of the X-rays from the focal spot to each detector, called a “ray,” increases in cross section from a point source to the receiving surface area of the detector, and thus is thought to magnify the density measurement because the receiving surface area of the detector area is larger than any cross sectional area of the object through which the ray passes.
As the disk rotates around the object being scanned, the scanner generates a plurality of projections at a corresponding plurality of projection angles. Using well-known algorithms, a CT image of the object may be generated from all the projection data collected at each of the projection angles. The CT image is representative of the density of a two dimensional “slice” of the object through which the fan beam has passed during the rotation of the disk through the various projection angles. The resolution of the CT image is determined in part by the width of the receiving surface area of each detector in the plane of the fan beam, the width of the detector being defined herein as the dimension measured in the same direction as the width of the fan beam, while the length of the detector is defined herein as the dimension measured in a direction normal to the fan beam parallel to the rotation, or Z-axis, of the scanner. In general, the resolution of the CT image is inversely proportional to the width of the receiving surface of each detector in the plane of the fan beam.
The CT scanner should provide images of sufficient resolution to detect plastic explosives on the order of only a few millimeters thick. Therefore, to provide adequate resolution, many revolutions are required. To meet high baggage throughput rates, a conventional CT baggage scanner such as the InVision Machine can only afford to generate a few CT images per bag. Clearly, one cannot scan the entire bag within the time allotted for a reasonably fast throughput. Generating only a few CT images per baggage items leaves most of the item unscanned and therefore does not provide scanning adequate to identify all potential threat objects in the bag, such as sheets of explosive material.
To improve throughput, the InVision Machine uses a pre-screening process which produces a two-dimensional projection image of the entire bag from a single angle. Regions of the projection identified as potentially containing threat items can then be subjected to a full scan or manual inspection. With this pre-screening and selective region scanning approach, the entire bag is not scanned, thus allowing potential threat items to pass through undetected. This is especially true in the case of sheet items oriented transversely to the direction of propagation of the radiation used to form the pre-screen projection and where the sheet covers a relatively large portion of the area of the bag.
Another baggage scanning system is described in an International Patent Application under the Patent Cooperation Treaty, document number WO 96/13017, published on May 2, 1996, entitled, “X-Ray Computed Tomography (CT) System for Detecting Thin Objects,” invented by Eberhard, et al. (referred to herein as the “Eberhard et al. system”). In the Eberhard, et al. system, an entire bag is subjected to a CT scan to generate voxel density data for the bag. A connected components labeling (CCL) process is then applied to the entire bag to identify objects by grouping voxels which are physically close together and which have densities within a predetermined range of densities. The voxels in each object are then counted to determine the volume of each object. If the volume of an object exceeds a threshold, the mass of the object is computed by multiplying the volume of each object voxel by its density and then totaling the individual voxel masses. If the mass of an object exceeds a mass threshold, the object is concluded to be a threat.
The Eberhard et al. publication teaches that its system can identify thin objects. The system sets its labeling density at a low level such that thin objects viewed edge-on which partially fill a voxel can be detected.
A significant drawback to the Eberhard et al. system is that it may miss thin objects such as sheet explosives that are not viewed edge-on and which cover a large area of the bag. These transversely oriented sheet objects will add only slightly to the density measured for the bag and will have only small density contrast with the background. If the density threshold used during CCL is set low enough to detect these sheets, then, because of the low contrast between the sheet and the background, the entire bag will be connected and labeled together, and no discernable object will be identified. If the threshold is set higher, then the sheet object will be missed.
Referring to the drawings, FIGS. 1, 2 and 3 show perspective, end cross-sectional and radial cross-sectional views, respectively, of a typical baggage scanning system 100, which includes a conveyor system 110 for continuously conveying baggage or luggage 112 in a direction indicated by arrow 114 through a central aperture of a CT scanning system 120. The conveyor system includes motor driven belts for supporting the baggage. Conveyer system 110 is illustrated as including a plurality of individual conveyor sections 122; however, other forms of conveyor systems may be used.
The CT scanning system 120 includes an annular shaped rotating platform, or disk, 124 disposed within a gantry support 125 for rotation about a rotation axis 127 (shown in FIG. 3) that is preferably parallel to the direction of travel 114 of the baggage 112. Disk 124 is driven about rotation axis 127 by any suitable drive mechanism, such as a belt 116 and motor drive system 118, or other suitable drive mechanism, such as the one described in U.S. Pat. No. 5,473,657 issued Dec. 5, 1995 to Gilbert McKenna, entitled “X-ray Tomographic Scanning System,” which is assigned to the present assignee and, which is incorporated herein in its entirety by reference. Rotating platform 124 defines a central aperture 126 through which conveyor system 110 transports the baggage 112.
The system 120 includes an X-ray tube 128 and a detector array 130 which are disposed on diametrically opposite sides of the platform 124. The detector array 130 is preferably a two-dimensional array, such as the array described in U.S. Pat. No. 6,091,795 entitled, “Area Detector Array for Computed Tomography Scanning System.” Other suitable arrays are known in the prior art. The system 120 further includes a data acquisition system (DAS) 134 for receiving and processing signals generated by detector array 130, and an X-ray tube control system 136 for supplying power to, and otherwise controlling the operation of, X-ray tube 128. The system 120 is also preferably provided with a computerized system (not shown) for processing the output of the data acquisition system 134 and for generating the necessary signals for operating and controlling the system 120. The computerized system can also include a monitor for displaying information including generated images. System 120 also includes shields 138, which may be fabricated from lead, for example, for preventing radiation from propagating beyond gantry 125.
The X-ray tube 128 may generate a pyramidally shaped beam, often referred to as a “cone beam,” 132 of X-rays that pass through a three dimensional imaging field, through which conveying system 110 transports baggage 112. After passing through the baggage disposed in the imaging field, detector array 130 receives cone beam 132 and generates signals representative of the densities of exposed portions of baggage 112. The beam therefore defines a scanning volume of space. Platform 124 rotates about its rotation axis 127, thereby transporting X-ray source 128 and detector array 130 in circular trajectories about baggage 112 as the conveyor system 110 continuously transports baggage through central aperture 126, so as to generate a plurality of projections at a corresponding plurality of projection angles.
Techniques using dual energy X-ray sources are known for providing additional information about a material's characteristics, beyond solely a density measurement. Techniques using dual energy X-ray sources involve measuring the X-ray absorption characteristics of a material for two different energy levels of X-rays. Depending upon the calibration of the scanner, dual energy measurements provide an indication of dual parameters of the material being scanned. For example, at one calibration setting, the dual parameters can be chosen to be the material's effective atomic number (Z is denoted as “effective atomic number”) and the material's density. At another calibration setting, the dual parameters can be chosen to be the material's photoelectric coefficients and the material's Compton coefficients. At yet another calibration setting, the dual parameters can be chosen to be an amount of a first material present (e.g., plastic) and an amount of a second material present (e.g., aluminum). Dual energy X-ray techniques for energy-selective reconstruction of X-ray Computer Tomography (hereinafter referred to as CT) images are described, for example, in Robert E. Alvarez and Albert Macovski, “Energy-selective Reconstructions in X-ray Computerized Tomography,” Phys. Med. Biol. 1976, Vol. 21, No. 5, 733-744; and U.S. Pat. Nos. 4,029,963 and 5,132,998. One algorithm used to generate such dual parameters from dual energy X-ray projection data is known as the Alvarez/Macovski Algorithm (hereinafter referred to as AMA). Others are known in the art.
One proposed use for such dual energy techniques has been in connection with a baggage scanner for detecting the presence of explosives in baggage. Explosive materials are generally characterized by a known range of atomic numbers and are therefore amenable to detection by such dual energy X-ray sources. One such dual energy source is described in U.S. Pat. No. 5,661,774, entitled “Improved Dual Energy Power Supply,” assigned to the present assignee and incorporated herein by reference. When dual energy scanning mode is configured for the system as depicted in FIGS. 1, 2 and 3, the control system 136 supplies modulated high voltages with respect to alternating projection angles to the X-ray tube 128. The detector array 130 then receives data corresponding to high-energy and low-energy X-ray spectra in alternating projection angles. Other dual energy sources are known in the art.
Post-reconstruction analysis and pre-reconstruction analysis are the two prior art techniques generally recognized for using dual energy X-ray sources in materials analysis (e.g., in a baggage scanner for detecting the presence of explosives in baggage). In post-reconstruction analysis, the signal flow is as shown in FIG. 4. The scanner 120 is typically similar to the one shown in FIGS. 1-3 and has an X-ray source capable of producing a fan or cone beam at two distinct energy levels (i.e., dual energy). The DAS 134 gathers signals generated by detector array 130 at discrete angular positions of the rotating platform 124, and passes the signals to the pre-processing unit 206. The pre-processing unit 206 re-sorts the data it receives from the DAS 134 in order to optimize the sequence for the subsequent mathematical processing. The pre-processing unit 206 also corrects the data from the DAS 134 for detector temperature, intensity of the primary beam, gain and offset, and other deterministic errors. Finally, the pre-processing unit 206 extracts data corresponding to high-energy views and routes it to a high-energy path 208, and routes the data corresponding to low-energy views to a low-energy path 210. A first reconstruction computer 218 receives the projection data from the high-energy path 208 and generates a CT image IH 226 corresponding to the high-energy series of projections. A second reconstruction computer 220 receives the projection data from the low-energy path 210 and generates a CT image IL 224 corresponding to the low-energy series of projections. A post-processing unit 230 receives the high-energy CT image 226 and the low-energy CT image 224 and performs voxel-by-voxel processing to yield the effective atomic number (Z is denoted as effective atomic number) image Iz 232. The Z image 232 and the high-energy CT image 226 can be provided to operators on a display 240, and both images can be used for automatic explosive detection in 238 as well. The images from the post-reconstruction analysis usually do not yield accurate estimates of the material's effective atomic number, and suffer low SNR (Signal to Noise Ratio) and many artifacts as well.
In pre-reconstruction analysis, the signal flow is as shown in FIG. 5. As is described herein for pre-reconstruction analysis, the dual energy decomposition computer 212 receives the projection data on the high-energy path 208 and the low-energy path 210 and performs the Alvarez/Macovski Algorithm to produce a first stream of projection data Ac 214, which is dependent on a first parameter of the material being scanned, and a second stream of projection data Ap 216, which is dependent on a second parameter of the material scanned. The first material parameter is often the Compton coefficient ac, and the second material parameter is often the photoelectric coefficient ap. A first reconstruction computer 219 receives the first stream of projection data 214 and generates a Compton image Ic 227 from the series of projections corresponding to the first material parameter. A second reconstruction computer 221 receives the second stream of projection data 216 and generates a photoelectric image Ip 225 from the series projections corresponding to the second material parameter. The third reconstruction computer 218 receives the stream of projection data 208 and generates a high-energy CT image IH 226. The two images 225 and 227 are processed in the post-processing unit 230 to yield a Z image Iz 232. The High-energy CT image 226 and the Z image 232 can be provided to operators on a display 240, and both images can be used for automatic explosive detection in detection unit 238 as well. The pre-reconstruction analysis yields better estimates of material's effective atomic number than the post-reconstruction analysis. However the pre-reconstruction analysis requires one more reconstruction computer than the post-reconstruction analysis.
Various approaches have been used for decomposition of the input projection data PL and PH into Compton projections Ac and photoelectric projections Ap. For example, the AMA method approximates PL and PH using polynomial functions in terms of Ac and Ap. The coefficients of the polynomial functions are determined through a calibration procedure as follows. By measuring the projection values of the combination of various thicknesses of two known materials, the coefficients can be calculated through a polynomial least squares fitting between the measured and modeled PL and PH. Once the coefficients of the polynomial functions are determined, the decomposition of the Compton and Photoelectric projections Ac and Ap from projections PL and PH is usually solved using the Newton-Raphson method.
Another prior art method of performing decomposition is the direct approximation method, discussed in L. A. Lehmann, R. E. Alvarez, A. Macovski, W. R. Brody, N. J. Pelc, S. J. Riederer, and A. L. Hall, Generalized Image Combinations In Dual KVP Digital Radiography, Med. Phys. 8, 659-667 (1981). In the direct approximation method, Ac and Ap are approximated as polynomial functions in terms of PL and PH. The coefficients of the polynomial functions in the direct approximation method are determined through a calibration procedure by measuring the projection values of the combination of various thicknesses of two known materials.
In yet another prior art method, decomposition is accomplished using iso-transmission lines, described K. Chuang and H. K. Huang, A Fast Dual-Energy Computational Method Using Isotransmission Lines and Tables, Med. Phys. 14, 186-192 (1987). According to this method, for a given projection value, an isotransmission line is represented by a linear equation in two basis functions. The isotransmission line method requires a large amount of calibration data. Further, the isotransmission line becomes increasingly non-linear as the projection value increases. In such a situation, the linear equations are not valid and the method causes large approximation errors.
CT images and Z (effective atomic number) images can be generated from both the pre-reconstruction and post-reconstruction analysis. The CT images measure the CT number of scanned materials, which approximates the density of the materials within each pixel or voxel; and the Z image measures the effective atomic number of the scanned materials within each pixel or voxel. The measurements of both CT number and Z can be used for automatic explosive detection.
In the assignee's single energy CT baggage scanning system as described and claimed in the U.S. patent applications listed above and incorporated herein by reference, single energy CT images without atomic number (Z) images are used to identify and classify threat items such as explosives by analyzing mass and/or density of identified objects in general. Voxels in CT data for a piece of baggage are associated with density values. Voxels having density values within certain predetermined ranges of density value can be identified and grouped together as objects. After objects are thus identified, a discrimination approach is applied in which identified objects can be classified as to whether they pose a threat. Using voxel volumes and masses of identified objects are compared to predetermined mass thresholds. Analysis of this comparison and other predetermined discrimination parameters, such as mean and standard deviation of the density, is used to determine whether the identified object can be classified as a threat object.
With the dual energy CT scanner producing both the CT image and the Z image, it is beneficial to have the detection system to use both types of images for threat detection to reduce false alarm rate, thus lowering the labor cost for checked luggage screening.
The mean and standard deviation of the measured density and atomic number of a segmented object usually do not extract enough information of the object to be classified, thus resulting in a high false alarm rate of the explosive detection system.
Since CT scanners are not perfect imaging devices, they generate artifacts in reconstructed images. For example, when a long cylindrical object is scanned with the long axis in the x-y plane of the scanner coordinate system, there is a severe cupping artifact caused by the beam hardening effect. In such a case, even if the object has uniform density i.e. having a low standard deviation of the physical density, it yields a much higher standard deviation of the density of the object calculated from the CT image. Therefore, one can not tell from the standard deviation of the measured density whether an object has a non-uniform physical density or has a uniform density affected by the beam hardening artifact.
Objects usually comprise parts or portions that are of different densities from each other. For example, a bottle containing liquor as one object at least can be divided into two portions: one portion is the bottle, which is made of glass, and the other portion is the liquid liquor. These two portions are physically very different. They are different in the density, atomic number, uniformity of the density and atomic number as well. A segmentation algorithm usually fails to segment them into two different objects. Sometimes it is actually desirable not to segment them into different objects and is preferred to treat them as a single object for detection. With both the glass bottle and the liquid liquor, it is easier to tell it is a bottle of liquor than with only either one part. However, using the mean and standard deviation of the density and atomic number measurements one can not tell the difference between a bottle containing liquor from a chunk of plastic explosive.
Thus, it is desirable to use other statistics derived from the density and atomic number measurements representing richer information of the segmented object for discriminating threats from non-threats so as to further reduce the false alarm rate.